Ansh Mittal (@AnshMittal1811)
  • Stars
    star
    208
  • Global Rank 119,581 (Top 5 %)
  • Followers 55
  • Following 11
  • Registered over 7 years ago
  • Most used languages
    Python
    26.7 %
  • Location 🇮🇳 India
  • Country Total Rank 3,115
  • Country Ranking

Top repositories

1

MachineLearning-AI

This repository contains all the work that I regularly did and studied from Medium blogs, several research papers, and other Repos (related/unrelated to the research papers).
168
star
2

100_Days_for_ComputerVision_Papers

This is a repo where I keep a track of the Computer Vision papers that I am reading
7
star
3

DLinComputerVision

3
star
4

AnshMittal1811

The front page of my GitHub ReadMe. Feel free to use it as you like.
3
star
5

Pytorch

Jupyter Notebook
2
star
6

Spring2022SentimentAnalysis

Jupyter Notebook
1
star
7

NLP

Python
1
star
8

daMCONCNN

Jupyter Notebook
1
star
9

PneumoniaModelsAnalysis

1
star
10

DeepLearningProjects

Jupyter Notebook
1
star
11

DataDrivenAstronomy

Jupyter Notebook
1
star
12

HandwrittenEquationSolver

1
star
13

BrainTumorClassification

This is the code and figures for the paper "AiCNNs (Artificially-integrated Convolutional Neural Networks) for Brain Tumor Prediction".
Jupyter Notebook
1
star
14

Tensorflow-Advanced-Techniques

Jupyter Notebook
1
star
15

QuantumMLSSQiskit

Jupyter Notebook
1
star
16

AdvancedMLSpecialization

Jupyter Notebook
1
star
17

Computer-aidedDiseaseRecognition

1
star
18

ContinualLearning

1
star
19

GANs-Specialization

Jupyter Notebook
1
star
20

NLPSpecialization

Python
1
star
21

100daysofdevops

Different Concepts related to Machine Learning Infrastructure, MLOps, and Machine Learning Deployment.
Python
1
star
22

AIHybridFullWorldModel

My First AI project done by referencing the model explained in https://worldmodels.github.io/. I'm really thankful to all the authors of this work. This is by no means my own work. It's just restructured and the CNN-VAE and MDN-RNN main codes have been coded by myself which is also annotated by comments.
Python
1
star
23

PneumoniaDetection

The URL for the paper corresponding to this work is given in the following URL: https://www.mdpi.com/1424-8220/20/4/1068. The model described in this paper can only distinguish between Pneumonia and Normal X-ray scans. This paper achieves an accuracy of approximately 96.36 % when detecting pneumonia from chest x-ray images using E4CC.
Jupyter Notebook
1
star